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kiwiPy: Robust, high-volume, messaging for big-data and computational science workflows [article]

Martin Uhrin, Sebastiaan P. Huber
2020 arXiv   pre-print
In this work we present kiwiPy, a Python library designed to support robust message based communication for high-throughput, big-data, applications while being general enough to be useful wherever high-volumes of messages need to be communicated in a predictable manner. KiwiPy relies on the RabbitMQ protocol, an industry standard message broker, while providing a simple and intuitive interface that can be used in both multithreaded and coroutine based applications. To demonstrate some of
more » ... s functionality we give examples from AiiDA, a high-throughput simulation platform, where kiwiPy is used as a key component of the workflow engine.
arXiv:2005.07475v1 fatcat:hbtx3lw2czcfborzo7vyn4idtq

Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows

Martin Uhrin, Sebastiaan P. Huber, Jusong Yu, Nicola Marzari, Giovanni Pizzi
2021 Computational materials science  
51NF40-182892), the European Centre of Excellence MaX "Materials design at the Exascale" (Grant No. 824143), by the Swiss Platform for Advanced Scientific Computing (PASC) and by the swissuniversities P-  ...  Sebastiaan P. Huber: Conceptualization, Software, Writing -original draft. Jusong Yu: Software, Writing -review & editing.  ... 
doi:10.1016/j.commatsci.2020.110086 fatcat:q53uyyiiv5cndevlirg7gi4qti

Materials Cloud, a platform for open computational science [article]

Leopold Talirz, Snehal Kumbhar, Elsa Passaro, Aliaksandr V. Yakutovich, Valeria Granata, Fernando Gargiulo, Marco Borelli, Martin Uhrin, Sebastiaan P. Huber, Spyros Zoupanos, Carl S. Adorf, Casper W. Andersen, Ole Schütt (+7 others)
2020 arXiv   pre-print
), the European Centre of Excellence MaX "Materials design at the Exascale" (grant no. 824143), the "MaGic" project of the European Research Council (grant agreement ID 666983), the swissuniversities P-  ... 
arXiv:2003.12510v1 fatcat:w5fgpmixyrctdhkhidh6pvfj4i

Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows [article]

Martin Uhrin and Sebastiaan P. Huber and Jusong Yu and Nicola Marzari and Giovanni Pizzi
2020 arXiv   pre-print
l e _ o f _ t h r e e _ a n d _ f i v e ) ( 5 cls . report_fizz_buzz , 6 ) . elif_ ( cls . i s _ m u l t i t p l e _ o f _ t h r e e ) ( 7 cls . report_fizz , 8 ) . elif_ ( cls . i s _ m u l t i p l e  ...  the syntax of the work chain outline: 1 spec . outline ( 2 cls . intialize_to_zero , 3 while_ ( cls . i s _ l e s s _ t h a n _ o r _ e q u a l _ t o _ h u n d r e d ) ( 4 if_ ( cls . i s _ m u l t i p  ... 
arXiv:2007.10312v2 fatcat:lx5ik452ejbyte2snu67bqfcuu

Workflow Engineering in Materials Design within the BATTERY 2030 + Project

Joerg Schaarschmidt, Jie Yuan, Timo Strunk, Ivan Kondov, Sebastiaan P. Huber, Giovanni Pizzi, Leonid Kahle, Felix T. Bölle, Ivano E. Castelli, Tejs Vegge, Felix Hanke, Tilmann Hickel (+3 others)
2021 Advanced Energy Materials  
Experimental efforts to develop and design new materials are increasingly complemented by computational strategies. This mirrors the trend in many other application areas, where computer-aided design has significantly accelerated product development, often reducing the cost at the same time. Examples are the automotive, aerospace, and electronics industries, where the development of novel products are nowadays unthinkable without computer-aided design. A prerequisite for the successful
more » ... on of such a strategy is the availability of predictive simulation protocols, which can be used as digital twins [3, 4] for devices in the context of development and design. Materials design is still behind other fields in the application of computeraided design strategies, not for the lack of effort, but because of the complexity of the underlying task. The computational challenges for understanding the material properties encompass interdisciplinary research, where the comprehension of its nature runs through different scales of materials behavior, requiring multi-scale approaches. However, the field is lacking a monolithic computational framework to cover all of these scales, in both space and time, with the available computational resources. [5] recent years, modeling and simulation of materials have become indispensable to complement experiments in materials design. High-throughput simulations increasingly aid researchers in selecting the most promising materials for experimental studies or by providing insights inaccessible by experiment. However, this often requires multiple simulation tools to meet the modeling goal. As a result, methods and tools are needed to enable extensive-scale simulations with streamlined execution of all tasks within a complex simulation protocol, including the transfer and adaptation of data between calculations. These methods should allow rapid prototyping of new protocols and proper documentation of the process. Here an overview of the benefits and challenges of workflow engineering in virtual material design is presented. Furthermore, a selection of prominent scientific workflow frameworks used for the research in the BATTERY 2030+ project is presented. Their strengths and weaknesses as well as a selection of use cases in which workflow frameworks significantly contributed to the respective studies are discussed.
doi:10.1002/aenm.202102638 fatcat:sp3dtziirrfvphvpblgrzun3oa

Materials Cloud, a platform for open computational science

Leopold Talirz, Snehal Kumbhar, Elsa Passaro, Aliaksandr V Yakutovich, Valeria Granata, Fernando Gargiulo, Marco Borelli, Martin Uhrin, Sebastiaan P Huber, Spyros Zoupanos, Carl S Adorf, Casper Welzel Andersen (+8 others)
2020 Scientific Data  
Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts (1) archival and dissemination services for raw and curated data, together with their provenance graph, (2) modelling services and virtual machines, (3) tools for data analytics, and pre-/post-processing, and (4) educational materials. Data is citable and archived persistently, providing a comprehensive embodiment of entire
more » ... ulation pipelines (calculations performed, codes used, data generated) in the form of graphs that allow retracing and reproducing any computed result. When an AiiDA database is shared on Materials Cloud, peers can browse the interconnected record of simulations, download individual files or the full database, and start their research from the results of the original authors. The infrastructure is agnostic to the specific simulation codes used and can support diverse applications in computational science that transcend its initial materials domain.
doi:10.1038/s41597-020-00637-5 pmid:32901046 pmcid:PMC7479138 fatcat:wggd4mdjv5dj5kvbh4cguvayoi

Common workflows for computing material properties using different quantum engines [article]

Sebastiaan P. Huber, Emanuele Bosoni, Marnik Bercx, Jens Bröder, Augustin Degomme, Vladimir Dikan, Kristjan Eimre, Espen Flage-Larsen, Alberto Garcia, Luigi Genovese, Dominik Gresch, Conrad Johnston (+14 others)
2021 arXiv   pre-print
_ s t a n d a r d _ p s m l " pseudos from P s e u d o D o j o" Listing 10.  ...  An example is shown in Listing 6. g e t _ i n p u t _ g e n e r a t o r() 2 i n p u t _ g e n. g e t _ r e l a x _ t y p e s() Listing 6.  ...  -p p r e c i s i o n Listing 9.  ... 
arXiv:2105.05063v1 fatcat:3sbr4pl5mnc23g2alkq3xtybtm

Aiida And The Materials Cloud: Workflow Engine With Automated Provenance And Dissemination Platform For Open Science

Sebastiaan P. Huber, Spyros Zoupanos, Leonid Kahle, Martin Uhrin, Nicolas Mounet, Rico Andreas Häuselmann, Snehal Kumbhar, Leopold Talirz, Aliaksandr Yakutovich, Elsa Passaro, Marco Borelli, Fernando Gargiulo (+9 others)
2018 Zenodo  
Modern advances in computational technology have facilitated great strides in a wide variety of scientific disciplines and have led to the production of a wealth of valuable research data. However, the extraordinarily quick growth of computational capabilities has left the scientific world wanting for a simple yet effective way of managing these new workflows and the vast amount of data that they produce. We present AiiDA[1], a highly-automated and robust workflow engine written in Python,
more » ... ned for high-throughput computational science. AiiDA automatically tracks data provenance (and stores it in the form of a directed graph) while managing and automating simulations running either locally or on supercomputers. All data and calculations are stored in a database and can be efficiently queried thanks to a simple but powerful query language. AiiDA enables computational science that is fully reproducible and facilitates sharing of research results. Its symbiotic counterpart, the Materials Cloud [2], is an interactive online platform powered by AiiDA. It is designed to enable seamless sharing and dissemination of resources, of raw data with their provenance as well as of curated open research data in computational science, and to provide cloud resources for simulations. The combination of AiiDA and Materials Cloud (whose architecture is shown in the figure) provides an Open Science Framework fully compliant with the FAIR (findable, accessible, interoperable and reusable) data principles [3]. The diligent and dedicated data management of AiiDA, combined with the user-friendly and ergonomic Materials Cloud, form an invaluable tool to any computational scientist. [1] G. Pizzi et al., Comp. Mat. Sci. 111, 218 (2016) - www.aiida.net [2] http://www.materialscloud.org [3] M. D. Wilkinson et al, Sci. Data 3, 160018 (2016)
doi:10.5281/zenodo.1311933 fatcat:ggiclcwl5vbbdlz4sseeqfza4i

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance [article]

Sebastiaan. P. Huber, Spyros Zoupanos, Martin Uhrin, Leopold Talirz, Leonid Kahle, Rico Häuselmann, Dominik Gresch, Tiziano Müller, Aliaksandr V. Yakutovich, Casper W. Andersen, Francisco F. Ramirez, Carl S. Adorf, Fernando Gargiulo, Snehal Kumbhar (+7 others)
2020 arXiv   pre-print
Additional support was provided by the "MaGic" project of the European Research Council (grant agreement ID 666983), the swissuniversities P-5 "Materials Cloud" project (grant agreement ID 182-008), the  ...  The web server is implemented using the flask (palletsprojects.com/p/flask) web framework and a number of flask plugins (including flask-sqlalchemy to manage sessions to the database and flask-restful  ... 
arXiv:2003.12476v1 fatcat:ig6kkzbvjrbjrlqvusrkgjzsg4

Common workflows for computing material properties using different quantum engines

Sebastiaan P. Huber, Emanuele Bosoni, Marnik Bercx, Jens Bröder, Augustin Degomme, Vladimir Dikan, Kristjan Eimre, Espen Flage-Larsen, Alberto Garcia, Luigi Genovese, Dominik Gresch, Conrad Johnston (+14 others)
2021 npj Computational Materials  
provenance of P A , which actually runs two subprocesses (S A and S B ).  ...  A user of P A can now directly set the inputs through the top-level interface.  ... 
doi:10.1038/s41524-021-00594-6 fatcat:im3fvsf7qrgxzjhc3qmk5wwp5q

AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance

Sebastiaan P Huber, Spyros Zoupanos, Martin Uhrin, Leopold Talirz, Leonid Kahle, Rico Häuselmann, Dominik Gresch, Tiziano Müller, Aliaksandr V Yakutovich, Casper W Andersen, Francisco F Ramirez, Carl S Adorf (+10 others)
2020 Scientific Data  
The web server is implemented using the flask (palletsprojects. com/p/flask) web framework and a number of flask plugins (including flask-sqlalchemy to manage sessions to the database and flask-restful  ... 
doi:10.1038/s41597-020-00638-4 pmid:32901044 pmcid:PMC7479590 fatcat:5wx7ievq4vh3bda6c2grs6rsnq

Materials Cloud, a platform for open computational science

Leopold Talirz, Snehal Kumbhar, Elsa Passaro, Aliaksandr V. Yakutovich, Valeria Granata, Fernando Gargiulo, Marco Borelli, Martin Uhrin, Sebastiaan P. Huber, Spyros Zoupano, Carl S. Adorf, Casper W. Andersen (+8 others)
2020
), the European Centre of Excellence MaX "Materials design at the Exascale" (grant no. 824143), the "MaGic" project of the European Research Council (grant agreement ID 666983), the swissuniversities P-  ... 
doi:10.3929/ethz-b-000440189 fatcat:7bvimdzu45dmfakyiqa6w7xtgq

Common workflows for computing material properties using different quantum engines

Sebastiaan P. Huber, Emanuele Bosoni, Marnik Bercx, Jens Bröder, Augustin Degomme, Vladimir Dikan, Kristjan Eimre, Espen Flage-Larsen, Alberto Garcia, Luigi Genovese, Dominik Gresch, Conrad Johnston (+14 others)
2021
provenance of P A , which actually runs two subprocesses (S A and S B ).  ...  A user of P A can now directly set the inputs through the top-level interface.  ... 
doi:10.18154/rwth-2021-09421 fatcat:cxmxnzz3ijejhcpbl467udbx2a

The Strengths Use Scale: Psychometric Properties, Longitudinal Invariance and Criterion Validity

Llewellyn E. van Zyl, Diane Arijs, Matthew L. Cole, Aldona Gliíska-Newes, Lara C. Roll, Sebastiaan Rothmann, Rebecca Shankland, Jacqueline M. Stavros, Nicolas B. Verger
2021 Frontiers in Psychology  
Wood et al., 2011; Huber et al., 2017; Bu and Duan, 2020; Vuorinen et al., 2020) .  ...  Active strengths use therefore, has an invigorating effect (Huber et al., 2017) .  ... 
doi:10.3389/fpsyg.2021.676153 fatcat:lvzy4z7iznb6pfqohckwe5w3ty

Acknowledgement to Reviewers of Viruses in 2020

Viruses Editorial Office
2021 Viruses  
Desprès, Philippe Dopazo, Carlos P.  ...  Huang, Yong Hirsch, Hans Huang, Ziwei Hirsch, Ivan Hubai, András Hirsch, Judith Huber, Andrew Hirsch, Silvia Ayora Huber, Victor Hizi, Amnon Hufbauer, Martin Ho, Chak-Sum Hufton, Simon E.  ... 
doi:10.3390/v13010098 pmid:33445811 fatcat:rlaidcm7rfhfpo2xp6xcev6kry
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